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1,192 results for “multi-omics”
A Multi-Omics Approach Reveals Mechanisms of Nanomaterial Toxicity and Structure-Activity-Relationships in Alveolar Macrophages
<p>This deposit contains the proteomics and metabolomics data belonging to the publication with the title "A Multi-Omics Approach Reveals Mechanisms of Nanomaterial Toxicity and Structure-Activity-Relationships in Alveolar Macrophages".</p>
Multi-omic Mapping of Human Pancreatic Islet Endoplasmic Reticulum and Cytokine Stress Responses Provide Type 2 Diabetes Genetic Insights
<p>The following data accompanying the manuscript can be found here:</p> <ul> <li>Expression (bulk RNA-seq & scRNA-seq) matrices</li> <li>Chromatin accessibility (bulk ATAC-seq) matrices</li> <li>TDF files for IGV browser visualization of cis-regulatory elements</li> </ul>
Multi-omics with dynamic network biomarker algorithm prefigures organ-specific metastasis of lung adenocarcinoma
<p><span>Efficacious strategies for early detection of lung cancer metastasis are of significance for improving the survival of lung cancer patients. Utilizing two clinical cohorts of four major types of lung cancer distant metastases, with single-cell RNA sequencing (scRNA-seq) of primary lesions and liquid chromatography mass spectrometry data of sera, we identified the marker genes and serum secretome foreshadowing the lung cancer site-specific metastasis through dynamic network biomarker (DNB)</span> <span>algorithm. Also, we located the intermediate status of cancer cells, along with its gene signatures, in each metastatic state trajectory that cancer cells at this stage still had no specific organotropism. Furthermore, an integrated neural network model based on the filtered scRNA-seq data was successfully constructed and validated to predict the metastatic state trajectory of cancer cells. Overall, our study provided a new insight to locate the pre-metastasis status of lung cancer and primarily examined its clinical application value, contributing to the early detection of lung cancer metastasis in a more feasible and efficacious way.</span></p>
MRBIGR: a versatile toolbox for genetic causal inference from population-scale multi-omics data
<p>MRBIGR is a multifunctional toolkit for pre-GWAS, GWAS and post-GWAS of both traditional and multi-omics data. MRBIGR provides all the components needed to build a complete GWAS pipeline, and integrates with rich post-GWAS analysis tools such as QTL annotation and haplotype analysis. In particular, Mendelian randomization (MR) analysis, MR-based network construction, module identification and gene ontology analysis are proposed for further genetic regulation studies. Additionally, it also produces rich plots for visualization of the analysis results and other formatted data.</p> <p>This dataset is used to generate images in MRBIGR papers and can also serve as an example to demonstrate how to use MRBIGR.</p>
Data for: Single-cell multi-omics in the medicinal plant Catharanthus roseus
<p>Advances in omics technologies now permit the generation of highly contiguous genome assemblies, detection of transcripts and metabolites at the level of single cells and high-resolution determination of gene regulatory features. Here, using a complementary, multi-omics approach, we interrogated the monoterpene indole alkaloid (MIA) biosynthetic pathway in <em>Catharanthus roseus</em>, a source of leading anticancer drugs. We identified clusters of genes involved in MIA biosynthesis on the eight <em>C. roseus</em> chromosomes and extensive gene duplication of MIA pathway genes. Clustering was not limited to the linear genome, and through chromatin interaction data, MIA pathway genes were present within the same topologically associated domain, permitting the identification of a secologanin transporter. Single-cell RNA-sequencing revealed sequential cell-type-specific partitioning of the leaf MIA biosynthetic pathway that, when coupled with a single-cell metabolomics approach, permitted the identification of a reductase that yields the bis-indole alkaloid anhydrovinblastine. We also revealed cell-type-specific expression in the root MIA pathway.</p>
Joint analysis of GWAS and multi-omics QTL summary statistics reveals a large fraction of GWAS signals shared with molecular phenotypes
<p>Data relevant to Wu et al. "Joint analysis of GWAS and multi-omics QTL summary statistics reveals a large fraction of GWAS signals shared with molecular phenotypes". </p>
(Preprocessing) Single-Cell Multi-Omics Identifies Chronic Inflammation as a Driver of TP53 mutant Leukaemic Evolution
<p>Files and scripts for preprocessing of dataset related to our publication titled "Single-Cell Multi-Omics Identifies Chronic Inflammation as a Driver of <em>TP53 </em>mutant Leukaemic Evolution".</p>
Multi-omics analysis reveals attenuation of cellular stress by Empagliflozin in High Glucose-treated human cardiomyocytes.
<p>Mass spectrometry raw data for the manuscript <strong>Multi-omics analysis reveals attenuation of cellular stress by Empagliflozin in High Glucose-treated human cardiomyocytes.</strong></p>
Data used in "Multi-omic profiling reveals the endogenous and neoplastic responses to immunotherapies in cutaneous T cell lymphoma"
<p>Data generated from the clinical trials, CITN-10 (NCT02243579) and CITN-13 (NCT03063632), analyzing the in vivo responses to anti-PD-1 monotherapy or anti-PD-1 interferon-gamma combination therapy in patients with advanced mycosis fungoides and sezary syndrome. Data include mass cytometry files of PBMCs, Olink serum targeted proteomics, Nanostring targeted bulk transcriptomics of tumor biopsies, CODEX imaging of tumor biopsies, and TCR sequencing from peripheral blood and tumor biopsies. Please direct correspondences to DRG or EWN.</p>
Multi-omics data analysis for rare population inference using single-cell graph transformer
<p>## MarsGT: For rare cell identification from matched scRNA-seq (snRNA-seq) and scATAC-seq (snATAC-seq),includes genes, enhancers, and cells in a heterogeneous graph to simultaneously identify major cell clusters and rare cell clusters based on eRegulon.</p> <p>## Data Collection The data was collected using GEO Database.</p> <p>## Data Format The data is stored as TSV file and MTX file where each row represents a gene and each column represents a sample. </p> <p>## Variables - Gene IDs: Gene Symbols (e.g., MALAT1) - Sample IDs: Sample identifiers (e.g., AAACATGCAAATTCGT-1) - Expression level: Row gene expression level.</p>
Multi-omics to Predict Responses to Biologics in IBD
ClinicalTrials.gov study NCT05542459. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Integrative Multi-omics Analysis to Predict Monoclonal Gammopathies Clinical Evolution
ClinicalTrials.gov study NCT07214324. IPD Sharing: Not stated. Countries: 1. Publications: 7.
A Multi-omics Study of "Healthy" Premature CAD Patients
ClinicalTrials.gov study NCT06362278. IPD Sharing: NO. Countries: 1. Publications: 11.
Early Diagnosis of Small Pulmonary Nodules by Multi-omics Sequencing
ClinicalTrials.gov study NCT03320044. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Multi-omics Database Construction of Healthy Korean Volunteers
ClinicalTrials.gov study NCT06183697. IPD Sharing: NO. Countries: 1. Publications: 1.
COVID-2019 Vaccine Immune Response Base on Single Cell Multi-Omics
ClinicalTrials.gov study NCT04871932. IPD Sharing: NO. Countries: 1. Publications: 1.
Multi-omics Study of Early-stage Lung Cancer with Distinct Phenotypes
ClinicalTrials.gov study NCT06699979. IPD Sharing: NO. Countries: 1. Publications: 1.
A Study to Analyze Data on Metastatic Ovarian Cancer Using Multi-omics
ClinicalTrials.gov study NCT05251883. IPD Sharing: UNDECIDED. Countries: 1. Publications: 8.
Multi-omics Database for Integrative Microbiome Analysis in a Cohort of Korean Patients With Ankylosing Spondylitis
ClinicalTrials.gov study NCT06076083. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Research on Precise Immune Prevention and Treatment of Glioma Based on Multi-omics Sequencing Data
ClinicalTrials.gov study NCT04792437. IPD Sharing: NO. Countries: 1. Publications: 9.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.